An algebraic method for compressing symbolic data tables

Authors:
Yannis Tzitzikas
Affiliations:
(Tel.: +30 2810 391 621/ Fax: +30 2810 391 638/ tzitzik@ics.forth.gr/ http://www.ics.forth.gr/~tzitzik) Institut d'Informatique, Faculté/s Universitaires Notre Dame de la Paix, Rue Grandgagnag ...
Venue:
Intelligent Data Analysis - Analysis of Symbolic and Spatial Data
Year:
2006

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Abstract

Although symbolic data tables summarize huge sets of data they can still become very large in size. This paper proposes a novel technique for compressing a symbolic data table using the recently emerged Compound Term Composition Algebra. One advantage of CTCA is that the closed world hypotheses of its operations can lead to a remarkably high "compression ratio". The compacted form apart from having much lower storage space requirements, it allows designing more efficient algorithms for symbolic data analysis.